Haiti_MosqAbundanceStudy

This repository contains data and code associated with a spatial modeling study of mosquito abundance in Haiti. The study aims to understand the ecological and environmental drivers of six mosquito species based on species-specific environmental buffers and spatiotemporal covariates.

Repository Contents

• Datasets (6 CSV files)
  Each .csv file corresponds to one mosquito species captured in the field study. The datasets include:

  • Daily mosquito count data
  • Latitude and longitude coordinates of trap locations
  • Matched environmental covariate data extracted using species-specific buffer radii
    The covariates include ecological factors aligned with the spatiotemporal resolution of trapping events.

• Modeling and Figure Code (.Rmd file)
  The .Rmd file contains all code used to:

  • Fit statistical models of mosquito abundance
  • Perform model diagnostics and selection
  • Generate the final maps and figures presented in the associated manuscript

Data Description

Each species-specific dataset includes:

• Date: Date of mosquito collection
• Latitude / Longitude: Coordinates of the trap site
• Count: Number of mosquitoes captured (species-specific)
• Environmental covariates such as temperature, precipitation, NDVI, population density, elevation, etc., which have been extracted using buffer zones tailored to each species' known dispersal range

Species Covered

The following six species are included in this study:

1. Aedes aegypti
2. Aedes albopictus
3. Culex quinquefasciatus
4. Culex nigripalpus
5. Aedes mediovittatus
6. Psorophora columbiae

Usage Instructions

1. Clone the repository:

   git clone https://github.com/[YourUsername]/Haiti_MosqAbundanceStudy.git

2. Open the .Rmd file in RStudio.
3. Install any required R packages (listed at the top of the .Rmd file).
4. Knit the document to reproduce model outputs and figures.

Citation

If you use this code or data in your research, please cite the associated manuscript:

[Manuscript Citation Placeholder – update with DOI or full citation when available]

License

This project is licensed under the MIT License — feel free to use, modify, and distribute with attribution.

Contact

For questions or collaborations, please contact:
Ian Pshea-Smith
University of Florida
Email: [ianpsheasmith@ufl.edu]